
RLCache: Automated Cache Management Using Reinforcement Learning
This study investigates the use of reinforcement learning to guide a gen...
read it

Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
We study the problem of causal discovery through targeted interventions....
read it

Statistical Agnostic Mapping: a Framework in Neuroimaging based on Concentration Inequalities
In the 70s a novel branch of statistics emerged focusing its effort in s...
read it

ncRNA Classification with Graph Convolutional Networks
Noncoding RNA (ncRNA) are RNA sequences which don't code for a gene but...
read it

ResourceEfficient Neural Networks for Embedded Systems
While machine learning is traditionally a resource intensive task, embed...
read it

Advance Prediction of Ventricular Tachyarrhythmias using Patient Metadata and MultiTask Networks
We describe a novel neural network architecture for the prediction of ve...
read it

Continual Learning with Adaptive Weights (CLAW)
Approaches to continual learning aim to successfully learn a set of rela...
read it

The AnimalAI Environment: Training and Testing AnimalLike Artificial Cognition
Recent advances in artificial intelligence have been strongly driven by ...
read it

iUNets: Fully invertible UNets with Learnable Up and Downsampling
UNets have been established as a standard neural network design archite...
read it

MEME: Generating RNN Model Explanations via Model Extraction
Recurrent Neural Networks (RNNs) have achieved remarkable performance on...
read it

Should Artificial Intelligence Governance be Centralised? Design Lessons from History
Can effective international governance for artificial intelligence remai...
read it

Transformation Consistency Regularization A SemiSupervised Paradigm for ImagetoImage Translation
Scarcity of labeled data has motivated the development of semisupervise...
read it

Extracting more from boosted decision trees: A high energy physics case study
Particle identification is one of the core tasks in the data analysis pi...
read it

A Deterministic Approach to Avoid Saddle Points
Loss functions with a large number of saddle points are one of the main ...
read it

On instabilities of deep learning in image reconstruction  Does AI come at a cost?
Deep learning, due to its unprecedented success in tasks such as image c...
read it

Deep active inference agents using MonteCarlo methods
Active inference is a Bayesian framework for understanding biological in...
read it

Learning a SpatioTemporal Embedding for Video Instance Segmentation
We present a novel embedding approach for video instance segmentation. O...
read it

Stochastic Optimization for Regularized Wasserstein Estimators
Optimal transport is a foundational problem in optimization, that allows...
read it

Variational Crossdomain Natural Language Generation for Spoken Dialogue Systems
Crossdomain natural language generation (NLG) is still a difficult task...
read it

FastSCNN: Fast Semantic Segmentation Network
The encoderdecoder framework is stateoftheart for offline semantic i...
read it

Improving and Understanding Variational Continual Learning
In the continual learning setting, tasks are encountered sequentially. T...
read it

Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care
Clinical decision making is challenging because of pathological complexi...
read it

MixedVariable Bayesian Optimization
The optimization of expensive to evaluate, blackbox, mixedvariable fun...
read it

Universal Masking is Urgent in the COVID19 Pandemic: SEIR and Agent Based Models, Empirical Validation, Policy Recommendations
We present two models for the COVID19 pandemic predicting the impact of...
read it

On Learnability under General Stochastic Processes
Statistical learning theory under independent and identically distribute...
read it

SpatioTemporal Analysis of Facial Actions using LifecycleAware Capsule Networks
Most stateoftheart approaches for Facial Action Unit (AU) detection r...
read it

Dynamic Spectral Residual Superpixels
We consider the problem of segmenting an image into superpixels in the c...
read it

Adaptive Prediction Timing for Electronic Health Records
In realistic scenarios, multivariate timeseries evolve over casebycase...
read it

TwoStage Sparse Regression Screening to Detect BiomarkerTreatment Interactions in Randomized Clinical Trials
Highdimensional biomarkers such as genomics are increasingly being meas...
read it

Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks
Influence maximization is a widely studied topic in network science, whe...
read it

Deconfounding Reinforcement Learning in Observational Settings
We propose a general formulation for addressing reinforcement learning (...
read it

Improved Algorithm on Online Clustering of Bandits
We generalize the setting of online clustering of bandits by allowing no...
read it

Mimicry: Towards the Reproducibility of GAN Research
Advancing the state of Generative Adversarial Networks (GANs) research r...
read it

Masked Language Modeling for Proteins via Linearly Scalable LongContext Transformers
Transformer models have achieved stateoftheart results across a diver...
read it

AutoNCP: Automated pipelines for accurate confidence intervals
Successful application of machine learning models to realworld predicti...
read it

Path Integral Based Convolution and Pooling for Graph Neural Networks
Graph neural networks (GNNs) extends the functionality of traditional ne...
read it

A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector Spaces
Distributional word vectors have recently been shown to encode many of t...
read it

Variational Orthogonal Features
Sparse stochastic variational inference allows Gaussian process models t...
read it

βCores: Robust LargeScale Bayesian Data Summarization in the Presence of Outliers
Modern machine learning applications should be able to address the intri...
read it

Achieving Adversarial Robustness via Sparsity
Network pruning has been known to produce compact models without much ac...
read it

Scoring Lexical Entailment with a Supervised Directional Similarity Network
We present the Supervised Directional Similarity Network (SDSN), a novel...
read it

Creatures great and SMAL: Recovering the shape and motion of animals from video
We present a system to recover the 3D shape and motion of a wide variety...
read it

Superpixel Contracted GraphBased Learning for Hyperspectral Image Classification
A central problem in hyperspectral image classification is obtaining hig...
read it

Federated PCA with Adaptive Rank Estimation
In many online machine learning and data science tasks such as data summ...
read it

GraphX^NET Chest XRay Classification Under Extreme Minimal Supervision
The task of classifying Xray data is a problem of both theoretical and ...
read it

SemEval2013 Task 4: Free Paraphrases of Noun Compounds
In this paper, we describe SemEval2013 Task 4: the definition, the data...
read it

There is Strength in Numbers: Avoiding the HypothesisOnly Bias in Natural Language Inference via Ensemble Adversarial Training
Natural Language Inference (NLI) datasets contain annotation artefacts r...
read it

Principal Neighbourhood Aggregation for Graph Nets
Graph Neural Networks (GNNs) have been shown to be effective models for ...
read it

Sponge Examples: EnergyLatency Attacks on Neural Networks
The high energy costs of neural network training and inference led to th...
read it

Investigating 3D Atomic Environments for Enhanced QSAR
Predicting bioactivity and physical properties of molecules is a longsta...
read it
University of Cambridge
The University of Cambridge is a collegiate public research university in Cambridge, United Kingdom.